Abstract: Effective machine learning for natural hazard prediction and monitoring depends on timely access to high-quality, event-specific datasets and models capable of adapting to evolving ...

Abstract: Personalized learning has gained significant attention in recent years in response to the limitations of one-size-fits-all approaches to teaching, particularly in areas such as programming ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

If you’re learning machine learning with Python, chances are you’ll come across Scikit-learn. Often described as “Machine Learning in Python,” Scikit-learn is one of the most widely used open-source ...

The Department of Justice recently issued guidance encouraging federal agencies to use “artificial intelligence and machine translation to communicate with individuals who are limited English ...

When you install Python packages into a given instance of Python, the default behavior is for the package’s files to be copied into the target installation. But sometimes you don’t want to copy the ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

Ever wondered about that massive machine with a sliding barbell at the gym? Allow us to introduce you to the Smith machine. Despite being a staple in most gyms, this behemoth can be ...

Generate RDF graphs compliant with VEO. Validate and extend ontology-based models. Interface with SOSA, TIME, and GEO vocabularies. Simplify integration with machine learning workflows and early ...

ABSTRACT: In an era marked by rapid technological advancement, the fusion of Artificial Intelligence (AI), Machine Learning (ML), and Distributed Ledger Technology (DLT), commonly referred to as ...